Buscar en RiuNet

Listar

Todo RiuNet

Mi cuenta

Acceder

Ayuda RiuNet

Admin. UPV

Listar por palabra clave "Feature selection"

Mostrando ítems 1-19 de 19

A Multisensor System for Road Surface Identification

Safont, Gonzalo; Salazar Afanador, Addisson; Rodríguez, Alberto; Vergara Domínguez, Luís (IEEE, 2019-12-07)

[EN] This work introduces a multisensor road surface identification system that considers features from four different kind of sensors: microphones, accelerometers, speed signals, and handwheel signals. Features are extracted ...
A Study of Feature Selection Methods for Classification

Liu, Chenyu (Universitat Politècnica de València, 2022-05-10)

[ES] En este proyecto se implementarán varias técnicas de selección de características que se aplican para mejorar el rendimiento de la clasificación automática. Se analizarán varios problemas de clasificación de un ...
Algoritmos de Feature Selection utilizados en estimación de esfuerzo de proyectos de desarrollo software

Ajenjo Vicente, Iván Iñaki (Universitat Politècnica de València, 2020-10-06)

[ES] Hoy en día hay poco trabajo de investigación centrado en las técnicas de Feature Selection (FS), incluidas las características categóricas y continuas en la literatura de Estimación del esfuerzo de desarrollo de ...
Application of mutual information-based sequential feature selection to ISBSG mixed data

Fernández-Diego, Marta; González-Ladrón-de-Guevara, Fernando (Springer-Verlag, 2018)

[EN] There is still little research work focused on feature selection (FS) techniques including both categorical and continuous features in Software Development Effort Estimation (SDEE) literature. This paper addresses the ...
Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals

Nieto del-Amor, Félix; Beskhani, Raja; Ye Lin, Yiyao; Garcia-Casado, Javier; Díaz-Martínez, María del Alba; Monfort-Ortiz, Rogelio; Diago-Almela, Vicente Jose; Hao, Dongmei; Prats-Boluda, Gema (MDPI AG, 2021-09-10)

[EN] One of the remaining challenges for the scientific-technical community is predicting preterm births, for which electrohysterography (EHG) has emerged as a highly sensitive prediction technique. Sample and fuzzy entropy ...
Automated location of steel truss bridge damage using machine learning and raw strain sensor data

Parisi, F.; Mangini, A. M.; Fanti, M. P.; Adam, Jose M (Elsevier, 2022-06)

[EN] Strategic major infrastructure ageing requires structural health monitoring usage to avoid critical safety issues and disasters. Machine Learning can be a valuable tool to automate the process of analysing raw monitoring ...
Automatic sleep stages classification using EEG entropy features and unsupervised pattern analysis techniques

Rodríguez-Sotelo, Jose Luis; Osorio-Forero, Alejandro; Jiménez-Rodríguez, Alejandro; Cuesta Frau, David; Cirugeda Roldán, Eva María; Peluffo, Diego (MDPI, 2014)

Sleep is a growing area of research interest in medicine and neuroscience. Actually, one major concern is to find a correlation between several physiologic variables and sleep stages. There is a scientific agreement on the ...
Clasificación automática de registros ECG para la detección de Fibrilación Auricular y otros ritmos cardiacos

Jiménez Serrano, Santiago (Universitat Politècnica de València, 2018-10-23)

[ES] La importancia clínica de las arritmias cardiacas está aumentando, junto con su incidencia y prevalencia, principalmente asociadas con el envejecimiento de la población. Entre estas enfermedades destaca la Fibrilación ...
Combinación de modelos heterogéneos para la identificación de variantes genéticas implicadas en la diabetes mellitus tipo 2 (DT2)

Moltó Moltó, Jorge Ramón (Universitat Politècnica de València, 2023-10-05)

[ES] La genómica es la disciplina que estudia el genoma humano. Uno de los principales desafíos es: la detección de variables genéticas relevantes que determinen un genotipo o enfermedad. En este ámbito de estudio nos ...
Comparative modelling study on enantioresolution of structurally unrelated compounds with amylose-based chiral stationary phases in reversed phase liquid chromatography-mass spectrometry conditions

Perez-Baeza, Mireia; Escuder-Gilabert, Laura; Martín-Biosca, Yolanda; Sagrado Vives, Salvador; Medina-Hernández, María José (Elsevier, 2020-08-16)

[EN] Polysaccharide-based chiral stationary phases (CSPs) are the most used chiral selectors in HPLC. These CSPs can be used in normal, polar organic and aqueous-organic mobile phases. However, normal and polar organic ...
Comparison of ROC Feature Selection Method for the Detection of Decay in Citrus Fruit Using Hyperspectral Images

Lorente, D.; Blasco Ivars, José; Serrano López, Antonio José; Soria Olivas, Emilio; Aleixos Borrás, María Nuria; Gómez Sanchís, Juan (Springer Verlag, 2013-12)

Hyperspectral imaging systems allow to detect the initial stages of decay caused by fungi in citrus fruit automatically, instead of doing it manually under dangerous ultraviolet illumination, thus preventing the fungal ...
Desarrollo de nuevos marcadores y clasificadores de bajo coste computacional para identificar afecciones cardiacas en registros ECG

Jiménez Serrano, Santiago (Universitat Politècnica de València, 2023-09-07)

[ES] Las enfermedades cardiovasculares son una de las principales causas de mortalidad y morbilidad en el mundo. Entre las arritmias más comunes en adultos destaca la Fibrilación Auricular (FA), presentando una tendencia ...
Extracting Features from Textual Data in Class Imbalance Problems

Aravamuthan, Sarang; Jogalekar, Prasad; Lee, Jonghae (Universitat Politècnica de València, 2022-11-23)

[EN] We address class imbalance problems. These are classification problems where the target variable is binary, and one class dominates over the other. A central objective in these problems is to identify features that ...
Fall detection based on the gravity vector using a wide-angle camera

Bosch Jorge, Marc; Sánchez Salmerón, Antonio José; Valera Fernández, Ángel; Ricolfe Viala, Carlos (Elsevier, 2014-12)

Falls in elderly people are becoming an increasing healthcare problem, since life expectancy and the number of elderly people who live alone have increased over recent decades. If fall detection systems could be installed ...
First-Stage Prostate Cancer Identification on Histopathological Images: Hand-Driven versus Automatic Learning

García-Pardo, José Gabriel; Colomer, Adrián; Naranjo Ornedo, Valeriana (MDPI AG, 2019)

[EN] Analysis of histopathological image supposes the most reliable procedure to identify prostate cancer. Most studies try to develop computer aid-systems to face the Gleason grading problem. On the contrary, we delve ...
From 12 to 1 ECG lead: multiple cardiac condition detection mixing a hybrid machine learning approach with a one-vs-rest classification strategy

Jiménez-Serrano, Santiago; Rodrigo, Miguel; Calvo Saiz, Conrado Javier; Millet Roig, José; Castells, Francisco (IOP Publishing, 2022-06-30)

[EN] Objective: Detecting different cardiac diseases using a single or reduced number of leads is still challenging. This work aims to provide and validate an automated method able to classify ECG recordings. Performance ...
Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicillium digitatum and Penicillium italicum using the most relevant bands and non-linear classifiers

Gomez-Sanchis, J.; Blasco, J.; Soria-Olivas, E.; Lorente, D.; Escandell-Montero, P.; Martinez-Martinez, J. M.; Martinez-Sober, M.; Aleixos Borrás, María Nuria (Elsevier, 2013-08)

[EN] Green mold (Penicillium digitatum) and blue mold (Penicillium italicum) are important sources of postharvest decay affecting the commercialization of mandarins. These fungi infections produce enormous economic losses ...
Identificación de biomarcadores para el diagnóstico temprano del deterioro cognitivo leve en pacientes cirróticos con encefalopatía hepática mínima

Ferrer Ivorra, María Esperanza (Universitat Politècnica de València, 2016-05-19)

[EN] We work with a database of 143 biochemical compounds in two groups of patients with liver cirrhosis: 1) 26 patients with mild cognitive impairment, detected by performing psychometric tests and 2) 26 patients without ...
Machine learning models to predict nitrate concentration in a river basin

Dorado-Guerra, Diana Yaritza; Corzo-Pérez, Gerald; Paredes Arquiola, Javier; Pérez-Martín, Miguel Ángel (Institute of Physics Publishing Ltd., 2022-12-01)

[EN] Aquifer-stream interactions affect the water quality in Mediterranean areas; therefore, the coupling of surface water and groundwater models is generally used to solve water-planning and pollution problems in river ...